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      name:  <unnamed>
       log:  G:\MONKEY\Research\TPP\TPP.log
  log type:  text
 opened on:  26 Feb 2018, 16:03:38

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. *     ***************************************************************** *

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. *     ***************************************************************** *

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. *     File-Name:  TPP                                                   *

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. *     Date:       Febuary 2018                                          *

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. *     Author:     Eddie Hearn                                           *

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. *     Purpose:    Politics and Policy                                   *

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. *     Input File: TPP_PP.dta                                            *

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. *     Output File: TPP.log                                              *

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. *     Data Output: None                                                 *

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. *     Program:      Stata 14                                            *

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. *     Machine:    (HP)Office                                            *

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. *     ****************************************************************  *

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. *     ****************************************************************  *

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. use G:\MONKEY\Research\TPP\TPP_PP.dta

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. *     ****************************************************************  *

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. *                     Model 1 (basic)                                   *

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. *     ****************************************************************  *

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. probit 反対  b_per_farm b_GPP b_GAGG b_PAG b_col b_percap b_unemp b_nen DPJ new , vce(cluster 比例 )

Iteration 0:   log pseudolikelihood = -331.04205  
Iteration 1:   log pseudolikelihood = -273.94511  
Iteration 2:   log pseudolikelihood =  -273.7333  
Iteration 3:   log pseudolikelihood = -273.73282  
Iteration 4:   log pseudolikelihood = -273.73282  

Probit regression                               Number of obs     =        480
                                                Wald chi2(9)      =          .
                                                Prob > chi2       =          .
Log pseudolikelihood = -273.73282               Pseudo R2         =     0.1731

                                  (Std. Err. adjusted for 11 clusters in 比例)
------------------------------------------------------------------------------
             |               Robust
        反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  b_per_farm |   14.82879   3.288675     4.51   0.000     8.383108    21.27448
       b_GPP |   1.16e-09   3.41e-09     0.34   0.733    -5.51e-09    7.84e-09
      b_GAGG |   3.22e-07   3.33e-07     0.97   0.334    -3.31e-07    9.76e-07
       b_PAG |  -1.367374     5.1137    -0.27   0.789    -11.39004    8.655294
       b_col |   1.068874   3.571894     0.30   0.765     -5.93191    8.069659
    b_percap |  -.0377309   .1139691    -0.33   0.741    -.2611063    .1856446
     b_unemp |   18.73755   4.991262     3.75   0.000     8.954855    28.52024
       b_nen |  -.0519976   .0380182    -1.37   0.171    -.1265119    .0225167
         DPJ |  -1.221254    .237759    -5.14   0.000    -1.687253   -.7552546
         new |    .409137   .2346171     1.74   0.081    -.0507041    .8689782
       _cons |    1.10811   2.363247     0.47   0.639    -3.523768    5.739988
------------------------------------------------------------------------------

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. 
. 
. outreg2 using TPP1_3.doc, ctitle(Model 1)
TPP1_3.doc
dir : seeout

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. 
. 
. 
. 
. *     ****************************************************************  *

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. *                     Model 2 (Interaction)                             *

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. *     ****************************************************************  *

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. 
. 
. probit 反対  b_per_farm b_GPP b_GAGG b_PAG b_col b_percap b_unemp b_nen DPJ new SMD b_farmxSMD , vce(cluster 比例 )

Iteration 0:   log pseudolikelihood = -331.04205  
Iteration 1:   log pseudolikelihood = -267.76131  
Iteration 2:   log pseudolikelihood = -266.97424  
Iteration 3:   log pseudolikelihood = -266.95851  
Iteration 4:   log pseudolikelihood =  -266.9585  

Probit regression                               Number of obs     =        480
                                                Wald chi2(9)      =          .
                                                Prob > chi2       =          .
Log pseudolikelihood =  -266.9585               Pseudo R2         =     0.1936

                                  (Std. Err. adjusted for 11 clusters in 比例)
------------------------------------------------------------------------------
             |               Robust
        反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  b_per_farm |   4.916421   4.006453     1.23   0.220    -2.936082    12.76892
       b_GPP |  -1.51e-08   5.48e-09    -2.76   0.006    -2.59e-08   -4.37e-09
      b_GAGG |   3.13e-07   4.28e-07     0.73   0.464    -5.26e-07    1.15e-06
       b_PAG |  -5.662588   7.167172    -0.79   0.429    -19.70999     8.38481
       b_col |   1.007235   3.863189     0.26   0.794    -6.564477    8.578947
    b_percap |   .1260507   .1070518     1.18   0.239     -.083767    .3358685
     b_unemp |   26.35428   8.901377     2.96   0.003     8.907903    43.80066
       b_nen |  -.0925129   .0342572    -2.70   0.007    -.1596558     -.02537
         DPJ |  -1.188903   .2416554    -4.92   0.000    -1.662539   -.7152674
         new |   .4517765   .2113777     2.14   0.033     .0374839    .8660691
         SMD |  -1.226651   .2872988    -4.27   0.000    -1.789746   -.6635559
  b_farmxSMD |    11.4237   6.682024     1.71   0.087    -1.672823    24.52023
       _cons |   3.404904   2.143902     1.59   0.112    -.7970657    7.606874
------------------------------------------------------------------------------

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. 
. 
. outreg2 using TPP1_3.doc, append ctitle(Model 2)
TPP1_3.doc
dir : seeout

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. 
. 
. *     ****************************************************************  *

. 
. *                     Model 3 (Non clustered)                           *

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. *     ****************************************************************  *

. 
. 
. 
. probit 反対  b_per_farm b_GPP b_GAGG b_PAG b_col b_percap b_unemp b_nen DPJ new SMD b_farmxSMD, robust

Iteration 0:   log pseudolikelihood = -331.04205  
Iteration 1:   log pseudolikelihood = -267.76131  
Iteration 2:   log pseudolikelihood = -266.97424  
Iteration 3:   log pseudolikelihood = -266.95851  
Iteration 4:   log pseudolikelihood =  -266.9585  

Probit regression                               Number of obs     =        480
                                                Wald chi2(12)     =      97.99
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -266.9585               Pseudo R2         =     0.1936

------------------------------------------------------------------------------
             |               Robust
        反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  b_per_farm |   4.916421   7.870952     0.62   0.532    -10.51036     20.3432
       b_GPP |  -1.51e-08   6.91e-09    -2.19   0.029    -2.87e-08   -1.58e-09
      b_GAGG |   3.13e-07   3.04e-07     1.03   0.303    -2.83e-07    9.10e-07
       b_PAG |  -5.662588   5.107467    -1.11   0.268    -15.67304    4.347863
       b_col |   1.007235   3.018714     0.33   0.739    -4.909335    6.923806
    b_percap |   .1260507   .1237944     1.02   0.309    -.1165819    .3686834
     b_unemp |   26.35428   9.939051     2.65   0.008     6.874099    45.83446
       b_nen |  -.0925129   .0563791    -1.64   0.101     -.203014    .0179882
         DPJ |  -1.188903   .1889802    -6.29   0.000    -1.559298   -.8185088
         new |   .4517765   .1775022     2.55   0.011     .1038786    .7996744
         SMD |  -1.226651   .3675201    -3.34   0.001    -1.946977   -.5063249
  b_farmxSMD |    11.4237   6.651805     1.72   0.086    -1.613595      24.461
       _cons |   3.404904   2.916687     1.17   0.243    -2.311698    9.121506
------------------------------------------------------------------------------

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. 
. 
. outreg2 using TPP1_3.doc, append ctitle(Model 3)
TPP1_3.doc
dir : seeout

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. 
. 
. *     ****************************************************************  *

. 
. *                     Model 4 (reclasificantion of Zombie)              *

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. *     ****************************************************************  *

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. 
. 
. probit 反対  per_farm GPP Gross_AG per_ag collgrad per_cap per_unemp 歳 DPJ new SMD SMDXFarm , vce(cluster 比例 )

Iteration 0:   log pseudolikelihood = -331.04205  
Iteration 1:   log pseudolikelihood = -269.55594  
Iteration 2:   log pseudolikelihood = -269.17124  
Iteration 3:   log pseudolikelihood = -269.16854  
Iteration 4:   log pseudolikelihood = -269.16854  

Probit regression                               Number of obs     =        480
                                                Wald chi2(9)      =          .
                                                Prob > chi2       =          .
Log pseudolikelihood = -269.16854               Pseudo R2         =     0.1869

                                  (Std. Err. adjusted for 11 clusters in 比例)
------------------------------------------------------------------------------
             |               Robust
        反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    per_farm |    3.52735   4.389839     0.80   0.422    -5.076576    12.13128
         GPP |  -1.02e-08   5.86e-09    -1.74   0.082    -2.17e-08    1.30e-09
    Gross_AG |   4.69e-07   3.30e-07     1.42   0.155    -1.77e-07    1.11e-06
      per_ag |   -1.92754    4.25279    -0.45   0.650    -10.26286    6.407776
    collgrad |   1.560714   3.668089     0.43   0.670    -5.628608    8.750037
     per_cap |     .09826   .1225054     0.80   0.423    -.1418462    .3383662
   per_unemp |   23.33154   7.011563     3.33   0.001     9.589129    37.07395
          歳 |  -.0441332   .0302344    -1.46   0.144    -.1033914    .0151251
         DPJ |  -1.157362   .2408031    -4.81   0.000    -1.629327   -.6853964
         new |   .4563515   .2173949     2.10   0.036     .0302653    .8824376
         SMD |  -.7774932   .2379256    -3.27   0.001    -1.243819   -.3111677
    SMDXFarm |   10.25762   4.076658     2.52   0.012     2.267521    18.24773
       _cons |   .7591493   1.729647     0.44   0.661    -2.630896    4.149195
------------------------------------------------------------------------------

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. 
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. outreg2 using TPP4_5.doc, ctitle(Model 4)
TPP4_5.doc
dir : seeout

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. 
. 
. *     ****************************************************************  *

. 
. *                     Model 4B (reclasificantion no cluster)            *

. 
. *     ****************************************************************  *

. 
. probit 反対  per_farm GPP Gross_AG per_ag collgrad per_cap per_unemp 歳 DPJ new SMD SMDXFarm , robust

Iteration 0:   log pseudolikelihood = -331.04205  
Iteration 1:   log pseudolikelihood = -269.55594  
Iteration 2:   log pseudolikelihood = -269.17124  
Iteration 3:   log pseudolikelihood = -269.16854  
Iteration 4:   log pseudolikelihood = -269.16854  

Probit regression                               Number of obs     =        480
                                                Wald chi2(12)     =     100.42
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -269.16854               Pseudo R2         =     0.1869

------------------------------------------------------------------------------
             |               Robust
        反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    per_farm |    3.52735   6.702104     0.53   0.599    -9.608532    16.66323
         GPP |  -1.02e-08   5.90e-09    -1.73   0.084    -2.17e-08    1.38e-09
    Gross_AG |   4.69e-07   3.38e-07     1.39   0.165    -1.93e-07    1.13e-06
      per_ag |   -1.92754   7.288737    -0.26   0.791     -16.2132    12.35812
    collgrad |   1.560714   2.918088     0.53   0.593    -4.158632    7.280061
     per_cap |     .09826   .1245755     0.79   0.430    -.1459035    .3424235
   per_unemp |   23.33154   8.024968     2.91   0.004     7.602892    39.06019
          歳 |  -.0441332   .0514605    -0.86   0.391    -.1449939    .0567276
         DPJ |  -1.157362   .1886341    -6.14   0.000    -1.527078   -.7876458
         new |   .4563515   .1780034     2.56   0.010     .1074712    .8052317
         SMD |  -.7774932   .2485281    -3.13   0.002    -1.264599   -.2903871
    SMDXFarm |   10.25762   5.164442     1.99   0.047     .1355034    20.37974
       _cons |   .7591493   2.753492     0.28   0.783    -4.637596    6.155894
------------------------------------------------------------------------------

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. 
. 
. 
. 
. *     ****************************************************************  *

. 
. *                     Model 5 (Party Discipline Interaction)            *

. 
. *     ****************************************************************  *

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. 
. 
. 
. 
. probit 反対  b_per_farm b_GPP b_GAGG b_PAG b_col b_percap b_unemp b_nen DPJ new SMD b_farmxSMD  SMDXDPJ, vce(cluster 比例 )

Iteration 0:   log pseudolikelihood = -331.04205  
Iteration 1:   log pseudolikelihood = -267.18267  
Iteration 2:   log pseudolikelihood = -266.32388  
Iteration 3:   log pseudolikelihood = -266.30839  
Iteration 4:   log pseudolikelihood = -266.30838  

Probit regression                               Number of obs     =        480
                                                Wald chi2(9)      =          .
                                                Prob > chi2       =          .
Log pseudolikelihood = -266.30838               Pseudo R2         =     0.1955

                                  (Std. Err. adjusted for 11 clusters in 比例)
------------------------------------------------------------------------------
             |               Robust
        反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  b_per_farm |    4.96144   3.851145     1.29   0.198    -2.586666    12.50955
       b_GPP |  -1.47e-08   5.30e-09    -2.77   0.006    -2.51e-08   -4.29e-09
      b_GAGG |   3.09e-07   4.14e-07     0.75   0.455    -5.02e-07    1.12e-06
       b_PAG |  -5.296051   6.912733    -0.77   0.444    -18.84476    8.252657
       b_col |   .7079243   3.874212     0.18   0.855    -6.885391     8.30124
    b_percap |   .1172445    .100462     1.17   0.243    -.0796574    .3141465
     b_unemp |   26.02417    8.66908     3.00   0.003     9.033085    43.01526
       b_nen |  -.1017334   .0355005    -2.87   0.004    -.1713132   -.0321537
         DPJ |  -1.014766   .2876833    -3.53   0.000    -1.578615   -.4509169
         new |   .4386886   .2080994     2.11   0.035     .0308213    .8465559
         SMD |  -1.015055   .3418195    -2.97   0.003    -1.685009   -.3451015
  b_farmxSMD |    11.1857   6.641082     1.68   0.092    -1.830577    24.20198
     SMDXDPJ |  -.3138706   .2713375    -1.16   0.247    -.8456822    .2179411
       _cons |   3.828402   2.123353     1.80   0.071    -.3332935    7.990098
------------------------------------------------------------------------------

. 
. 
. 
. 
. 
. outreg2 using TPP4_5.doc, append ctitle(Model 5)
TPP4_5.doc
dir : seeout

. 
. 
. 
. *     ****************************************************************  *

. 
. *                    Model 5B (Party Discipline Interaction no cluster) *

. 
. *     ****************************************************************  *

. 
. probit 反対  b_per_farm b_GPP b_GAGG b_PAG b_col b_percap b_unemp b_nen DPJ new SMD b_farmxSMD  SMDXDPJ , robust

Iteration 0:   log pseudolikelihood = -331.04205  
Iteration 1:   log pseudolikelihood = -267.18267  
Iteration 2:   log pseudolikelihood = -266.32388  
Iteration 3:   log pseudolikelihood = -266.30839  
Iteration 4:   log pseudolikelihood = -266.30838  

Probit regression                               Number of obs     =        480
                                                Wald chi2(13)     =      98.40
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -266.30838               Pseudo R2         =     0.1955

------------------------------------------------------------------------------
             |               Robust
        反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  b_per_farm |    4.96144    7.78422     0.64   0.524    -10.29535    20.21823
       b_GPP |  -1.47e-08   6.83e-09    -2.15   0.032    -2.81e-08   -1.29e-09
      b_GAGG |   3.09e-07   3.01e-07     1.03   0.304    -2.80e-07    8.98e-07
       b_PAG |  -5.296051   5.067867    -1.05   0.296    -15.22889    4.636786
       b_col |   .7079243   3.024786     0.23   0.815    -5.220548    6.636397
    b_percap |   .1172445   .1218399     0.96   0.336    -.1215573    .3560463
     b_unemp |   26.02417   10.02992     2.59   0.009     6.365892    45.68245
       b_nen |  -.1017334   .0579173    -1.76   0.079    -.2152493    .0117824
         DPJ |  -1.014766     .24296    -4.18   0.000    -1.490959   -.5385729
         new |   .4386886   .1773164     2.47   0.013     .0911548    .7862224
         SMD |  -1.015055   .4076752    -2.49   0.013    -1.814084   -.2160267
  b_farmxSMD |    11.1857   6.558813     1.71   0.088    -1.669335    24.04074
     SMDXDPJ |  -.3138706     .27755    -1.13   0.258    -.8578585    .2301174
       _cons |   3.828402   2.970363     1.29   0.197    -1.993403    9.650208
------------------------------------------------------------------------------

. 
. 
. 
. 
. 
. 
. 
. 
. 
. *     ****************************************************************  *

. 
. *                   Marginal Effect                                     *

. 
. *     ****************************************************************  *

. 
. 
. 
. probit 反対  b_per_farm b_GPP b_GAGG b_PAG b_col b_percap b_unemp b_nen DPJ new SMD b_farmxSMD , vce(cluster 比例 )

Iteration 0:   log pseudolikelihood = -331.04205  
Iteration 1:   log pseudolikelihood = -267.76131  
Iteration 2:   log pseudolikelihood = -266.97424  
Iteration 3:   log pseudolikelihood = -266.95851  
Iteration 4:   log pseudolikelihood =  -266.9585  

Probit regression                               Number of obs     =        480
                                                Wald chi2(9)      =          .
                                                Prob > chi2       =          .
Log pseudolikelihood =  -266.9585               Pseudo R2         =     0.1936

                                  (Std. Err. adjusted for 11 clusters in 比例)
------------------------------------------------------------------------------
             |               Robust
        反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  b_per_farm |   4.916421   4.006453     1.23   0.220    -2.936082    12.76892
       b_GPP |  -1.51e-08   5.48e-09    -2.76   0.006    -2.59e-08   -4.37e-09
      b_GAGG |   3.13e-07   4.28e-07     0.73   0.464    -5.26e-07    1.15e-06
       b_PAG |  -5.662588   7.167172    -0.79   0.429    -19.70999     8.38481
       b_col |   1.007235   3.863189     0.26   0.794    -6.564477    8.578947
    b_percap |   .1260507   .1070518     1.18   0.239     -.083767    .3358685
     b_unemp |   26.35428   8.901377     2.96   0.003     8.907903    43.80066
       b_nen |  -.0925129   .0342572    -2.70   0.007    -.1596558     -.02537
         DPJ |  -1.188903   .2416554    -4.92   0.000    -1.662539   -.7152674
         new |   .4517765   .2113777     2.14   0.033     .0374839    .8660691
         SMD |  -1.226651   .2872988    -4.27   0.000    -1.789746   -.6635559
  b_farmxSMD |    11.4237   6.682024     1.71   0.087    -1.672823    24.52023
       _cons |   3.404904   2.143902     1.59   0.112    -.7970657    7.606874
------------------------------------------------------------------------------

. 
. drawnorm MG_b1-MG_b13, n(1000) means(e(b)) cov(e(V))clear
(obs 1,000)

. 
. save simulated_betas, replace
file simulated_betas.dta saved

. 
. gen marginal_effect = MG_b1+  MG_b12

. 
. centile marginal_effect, centile(0.5 2.5, 50, 97.5 99.5)

                                                       -- Binom. Interp. --
    Variable |       Obs  Percentile    Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
marginal_e~t |     1,000         .5    4.241666        2.473597    5.276493
             |                  2.5    6.932891        5.611356     7.45974
             |                   50    16.11918        15.78123    16.50313
             |                 97.5     25.7042        24.63753    26.31298
             |                 99.5    28.70841         27.2563    32.33425

. 
. 
. 
. clear

. 
. 
. 
. 
. 
. *     ****************************************************************  *

. 
. *                   Predicted Prob                                      *

. 
. *     ****************************************************************  *

. 
. 
. 
. 
. 
. use G:\MONKEY\Research\TPP\TPP_PP.dta

. 
. 
. 
. estsimp probit 反対  b_per_farm b_GPP b_GAGG b_PAG b_col b_percap b_unemp b_nen DPJ new SMD b_farmxSMD , robust

Iteration 0:   log pseudolikelihood = -331.04205
Iteration 1:   log pseudolikelihood = -268.87901
Iteration 2:   log pseudolikelihood = -267.04321
Iteration 3:   log pseudolikelihood = -266.95934
Iteration 4:   log pseudolikelihood =  -266.9585
Iteration 5:   log pseudolikelihood =  -266.9585

Probit regression                                 Number of obs   =        480
                                                  Wald chi2(12)   =      97.99
                                                  Prob > chi2     =     0.0000
Log pseudolikelihood =  -266.9585                 Pseudo R2       =     0.1936

------------------------------------------------------------------------------
             |               Robust
      反対 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  b_per_farm |    4.91642   7.870952     0.62   0.532    -10.51036     20.3432
       b_GPP |  -1.51e-08   6.91e-09    -2.19   0.029    -2.87e-08   -1.58e-09
      b_GAGG |   3.13e-07   3.04e-07     1.03   0.303    -2.83e-07    9.10e-07
       b_PAG |  -5.662588   5.107467    -1.11   0.268    -15.67304    4.347863
       b_col |   1.007235   3.018714     0.33   0.739    -4.909335    6.923805
    b_percap |   .1260507   .1237944     1.02   0.309    -.1165819    .3686834
     b_unemp |   26.35428   9.939052     2.65   0.008     6.874099    45.83447
       b_nen |  -.0925129   .0563791    -1.64   0.101     -.203014    .0179882
         DPJ |  -1.188903   .1889802    -6.29   0.000    -1.559298   -.8185088
         new |   .4517765   .1775022     2.55   0.011     .1038786    .7996744
         SMD |  -1.226651   .3675201    -3.34   0.001    -1.946977   -.5063249
  b_farmxSMD |    11.4237   6.651805     1.72   0.086    -1.613594      24.461
       _cons |   3.404904   2.916687     1.17   0.243    -2.311698    9.121506
------------------------------------------------------------------------------

Simulating main parameters.  Please wait....

Note: Clarify is expanding your dataset from 480 observations to 1000
observations in order to accommodate the simulations.  This will append
missing values to the bottom of your original dataset.

% of simulations completed: 7% 15% 23% 30% 38% 46% 53% 61% 69% 76% 84% 92% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13

. 
. 
. 
. setx median

. 
. setx SMD 1

. 
. 
. 
. setx b_per_farm .016 b_farmxSMD .016

. 
. simqi, genpr(smd25)

Simqi generated the following new variable(s): smd25

. 
. gen SMD25 = 1-smd25

. 
. sum SMD25

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       SMD25 |      1,000    .1654794     .042691   .0708274    .339648

. 
. 
. 
. setx b_per_farm .059 b_farmxSMD .059

. 
. simqi, genpr(smd75)

Simqi generated the following new variable(s): smd75

. 
. gen SMD75 = 1-smd75

. 
. sum SMD75

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       SMD75 |      1,000    .3871096      .06971   .1577851   .6130131

. 
. 
. 
. gen diff = SMD75 - SMD25

. 
. centile diff, centile(2.5, 50, 97.5)

                                                       -- Binom. Interp. --
    Variable |       Obs  Percentile    Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
        diff |     1,000        2.5     .059297        .0408013    .0714762
             |                   50    .2224796        .2153844    .2296569
             |                 97.5    .3870619        .3707222    .4088729

. 
. 
. 
. setx median

. 
. setx SMD  0

. 
. 
. 
. setx b_per_farm .016 b_farmxSMD 0

. 
. simqi, genpr(pr25)

Simqi generated the following new variable(s): pr25

. 
. gen PR25 = 1-pr25

. 
. sum PR25

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
        PR25 |      1,000    .5238243    .1045338   .1998413   .8127105

. 
. 
. 
. setx b_per_farm .059 b_farmxSMD 0

. 
. simqi, genpr(pr75)

Simqi generated the following new variable(s): pr75

. 
. gen PR75 = 1-pr75

. 
. sum PR75

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
        PR75 |      1,000    .5979395    .1060903   .2186506   .9049734

. 
. 
. 
. gen diffpr = PR75 - PR25

. 
. centile diffpr, centile(2.5, 50, 97.5)

                                                       -- Binom. Interp. --
    Variable |       Obs  Percentile    Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
      diffpr |     1,000        2.5   -.1852674       -.2072532   -.1663308
             |                   50    .0760284        .0672517    .0833647
             |                 97.5    .3313688        .3135765    .3479594

. 
. 
. 
. 
. 
. setx median

. 
. setx SMD  1

. 
. 
. 
. 
. 
. exit, clear
